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In the post-WTO era, the volume of international trade has grown in a good amount in India. At the same time, the continuous lowering and removing of the trade barriers of different forms create several impacts on poverty and inequality. In this chapter, we tried to capture the issues of inequality, specially the gender inequality, which has worsened a lot in the last two decades. In one side, trade openness enhanced the growth, but at the cost of increasing inequality. Theil index and Atkinson index both show an increasing trend of inequality. The Gender Inequality Index (GII) and the Inequality-adjusted Human Development or Gender Development Indices are also showing increasing inequality. The state-wise analysis of such inequality indices is varying a lot over the study period. This chapter throws some insight into these issues and concludes that in the post-WTO era income inequality has increased a lot with a very few exceptions. In some states (like Maharashtra, Gujarat, Karnataka, and Punjab) only export have increased the employment in the unorganized sectors. The study concludes that exports have generated additional employment and incomes in the economy, but these gains have not trickled down to the poor. The study is confined to Indian cases only and covers the time period 2000–2001 to 2018–2019.

Measures of inequality determine the effectiveness of social and economic policies aimed at reducing inequality and to design effective intervention policies. The purpose of this paper is to focus on poverty reduction and welfare improving impacts of reducing income inequality in the case of Fiji. Using Fiji's Household Income and Expenditure Survey 2002‐2003, a comprehensive analysis is used to measure the level of inequality by household income, quintile income distribution, decomposition of inequality by ethnicity and regional groups, and the household income inequality by source of income.

Several statistical techniques have been applied to investigate the degree of inequality in the household income. These include the Gini coefficient, the Nelson ratio, the concentration index and the Atkinson index. An evaluation by ethnicity, regions and household income sources reflects the level of inequality, and concerns for policies and governance.

The results show that urban households, in particular, experience greater inequalities, in both positive and normative terms. The Indo‐Fijian households experience greater income inequalities than the Fijian households. Decomposition results for the separate factor income components also indicate major sources of inequality. These findings clearly establish that Fiji still has a long way to go in reducing the income gaps between the rich and the poor in both rural and urban households.

The paper is a first study that estimates various measures of inequality in the case of Fiji. The implication of the empirical findings suggests that Fiji is unlikely to achieve its Millennium Development Goal of halving poverty rate by 2015 due to the large income differentials by ethnicity and in the urban‐rural areas.

This paper extends a methodology proposed by Nissanov and Silber (2009) who decomposed the coefficient β used in convergence analysis into three components checking respectively whether there was σ-convergence, whether ‘pure mobility’ (upward or downward income mobility) was lower among the poor and what the extent of ‘residual mobility’ (the third component) was.

The present paper extends this analysis by applying it to the analysis of regional per capita income levels but also to that of within regions inequality and regional welfare levels. The empirical illustration uses Portuguese data on average earnings at the level of NUTS3.

Health outcomes are often described according to two dimensions: quality of life and quantity of life. We analyze the measurement of inequality of health distributions referring to these two dimensions. Our analysis relies on a novel treatment of the quality-of-life dimension, which might not have a standard mathematical structure. We single out two families of (absolute and relative) multidimensional health inequality indices, inspired by the classical normative approach to income inequality measurement. We also discuss how to extend the analysis to deal with the related problem of health deprivation measurement in this setting.

This paper analyses the relative inequality of the personal income distribution in the EU15 and Member countries using the European Community Household Panel (1994–2001). We select well-known measures like the Gini and Atkinson indices and calculate the 95 percent confidence intervals. Whenever possible we identify unambiguous rankings; when this is not possible we explain the differences through their inequality sensitivity and normative meaning.

We find an important regional differences in income inequality when comparing Southern European countries with the Northern and Central European ones. In 2001, Southern Europe and the United Kingdom are the most unequal countries in spite of the fact that the majority of these countries enjoyed decreasing income inequality over the time period studied.

The distributional impacts of replacing an income tax that has graduated marginal rates by a flat tax are complex. Typically the flat tax rate will be less than the top marginal rate under the pre-existing tax, leading to gains for the wealthiest. On the other hand, real-world proposals generally combine this with increases in personal exemptions that benefit some of the lowest income taxpayers. The result is that flat tax proposals usually redistribute from the middle to the extremes.

We adopt a standard distributional impact methodology, based on Atkinson's cost of inequality approach, to estimate the degree of implicit redistribution created through public funding of health insurance in Canada. The first stage of the exercise is to determine the public health insurance benefits received by families of various age and composition and to add these to measured after-tax incomes. In our base case, which uses the Atkinson Mean Logarithmic Deviation as inequality index, we find that accounting for public health insurance benefits implies a reduction in inequality equivalent to 2.4% of per capita income. We then model the implications of moving to a hypothetical fully privatized system while proportionately refunding to individuals the tax revenues saved in doing so. This would give rise to a further 2.4% equivalent per capita income reduction resulting from increased inequality in the distribution of after-tax income. Thus, for this scenario, moving from public financing of health insurance in Canada to a fully privatized system implies an overall increase in inequality equivalent to a loss of 4.8% of per capita income. This corresponds to an increase of about 25% in existing inequality. Not surprisingly, the impact of publicly financed health insurance in reducing inequality is strongest for the elderly.

The last 20 years have seen a significant evolution in the literature on horizontal inequity (HI) and have generated two major and “rival” methodological strands, namely, classical HI and reranking. We propose in this paper a class of ethically flexible tools that integrate these two strands. This is achieved using a measure of inequality that merges the well-known Gini coefficient and Atkinson indices, and that allows a decomposition of the total redistributive effect of taxes and transfers into a vertical equity effect and a loss of redistribution due to either classical HI or reranking. An inequality-change approach and a money-metric cost-of-inequality approach are developed. The latter approach makes aggregate classical HI decomposable across groups. As in recent work, equals are identified through a non-parametric estimation of the joint density of gross and net incomes. An illustration using Canadian data from 1981 to 1994 shows a substantial, and increasing, robust erosion of redistribution attributable both to classical HI and to reranking, but does not reveal which of reranking or classical HI is more important since this requires a judgement that is fundamentally normative in nature.

Income inequality rose in Germany since the 1970s. To quantify the impact of different socio-economic trends on inequality, the author constructs counterfactual distributions of net household income with rich German data from the Microcensus in 1976 and 2011. The procedure allows to study the effect of marital sorting in education and includes indirect effects such as the influence of education on employment. When comparing the income distribution in West Germany for 1976 and 2011, the author finds that the prevalence of singlehood accounts to a large extent for the observed increase in inequality. The inequality increase is also associated with a change of employment among males and single females. When comparing West and East Germany in 2011, the author finds that the stronger labour market attachment of East German married females combined with the high East German unemployment produces even more income inequality than the West German employment structure. Moreover, the smaller household size boosts inequality in East Germany, whereas education works against it. In both comparisons, the author finds no significant impact of positive assortative mating in education or ageing.

The purpose of this paper is to investigate the effect of inequality on female employment in 42 countries in sub-Saharan Africa (SSA) for the period 2004–2014.

Three inequality indicators are used, namely, the: Gini coefficient, Atkinson index and Palma ratio. Two indicators of gender inclusion are also employed, namely: female employment and female unemployment rates. The empirical analysis is based on the generalised method of moments.

The following main findings are established. First, inequality increases female unemployment in regressions based on the Palma ratio. Second, from the robustness checks, inequality reduces female employment within the frameworks of the Gini coefficient and Palma ratio.

Studies on the relevance of income inequality on female economic participation in SSA are sparse.